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Read-back working.

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This commit is contained in:
Michael Marshall 2019-02-18 17:12:27 +00:00
parent c77069244d
commit 04b58de5de
3 changed files with 100 additions and 49 deletions
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62
Grid/serialisation/BaseIO.h
View File

@ -42,6 +42,7 @@ namespace Grid {
: std::integral_constant<bool, std::is_arithmetic<T>::value> {};
// Eigen tensors can be composed of arithmetic scalar and complex types
// TODO Support Grid::comples from GPU port
template<typename T> struct is_scalar : std::integral_constant<bool,
std::is_arithmetic<T>::value || is_complex<T>::value> {};
@ -202,10 +203,10 @@ namespace Grid {
Scalar * pScalar = ET.data();
for( std::size_t j = 0; j < NumScalars; j++ ) {
// if constexpr is C++ 17 ... but otherwise need two specialisations (Container vs Scalar)
if constexpr ( InnerRank == 0 ) {
if constexpr ( EigenIO::is_scalar<Scalar>::value ) {
lambda( * pScalar, Seq++, MyIndex );
} else {
for( typename Scalar::scalar_type &Source : * pScalar ) {
for( typename EigenIO::Traits<Scalar>::scalar_type &Source : * pScalar ) {
lambda(Source, Seq++, MyIndex );
// Now increment SubIndex
for( auto i = rank + InnerRank - 1; i != rank - 1 && ++MyIndex[i] == Dims[i]; i-- )
@ -244,7 +245,7 @@ namespace Grid {
std::cout << pName;
for( auto i = 0 ; i < rank; i++ ) std::cout << "[" << dims[i] << "]";
std::cout << " in memory order:" << std::endl;
for_all( t, [&](typename Traits::scalar_type &c, typename T::Index index, const std::array<size_t, T::NumIndices + Traits::rank_non_trivial> Dims ){
for_all( t, [&](typename Traits::scalar_type &c, typename T::Index index, const std::array<size_t, T::NumIndices + Traits::rank_non_trivial> &Dims ){
std::cout << " ";
for( auto dim : Dims )
std::cout << "[" << dim << "]";
@ -253,6 +254,16 @@ namespace Grid {
std::cout << "========================================" << std::endl;
}
template <typename T>
typename std::enable_if<!EigenIO::is_tensor<T>::value, void>::type
dump_tensor_func(T &t, const char * pName = nullptr)
{
std::cout << "Dumping non-tensor object ";
if( pName )
std::cout << pName;
std::cout << "=" << t;
}
// Helper to dump a tensor in memory order
// Kind of superfluous given the above ... just keeping in case I need to fall back to this
#define DumpMemoryOrder(args...) DumpMemoryOrder_func(args)
@ -379,12 +390,12 @@ namespace Grid {
template <typename ETensor>
typename std::enable_if<EigenIO::is_tensor_variable<ETensor>::value, void>::type
Reshape(ETensor &t, const std::array<typename ETensor::Index, ETensor::NumDimensions> &dims );
template <typename ETensor>
/*template <typename ETensor>
typename std::enable_if<EigenIO::is_tensor_fixed<ETensor>::value, std::size_t>::type
DimSize(ETensor &t, std::size_t dim );
template <typename ETensor>
typename std::enable_if<EigenIO::is_tensor_variable<ETensor>::value, std::size_t>::type
DimSize(ETensor &t, std::size_t dim );
DimSize(ETensor &t, std::size_t dim );*/
protected:
template <typename U>
void fromString(U &output, const std::string &s);
@ -677,43 +688,52 @@ namespace Grid {
Reader<T>::read(const std::string &s, ETensor &output)
{
// alias to element type
using Scalar = typename EigenIO::Traits<typename ETensor::Scalar>::scalar_type;
using Container = typename ETensor::Scalar;
using Traits = EigenIO::Traits<Container>;
using Scalar = typename Traits::scalar_type;
// read the (flat) data and dimensionality
std::vector<std::size_t> dimData;
std::vector<Scalar> buf;
upcast->readMultiDim( s, buf, dimData );
// Make sure that the number of elements read matches dimensions read
const std::size_t NumElements{buf.size()};
std::size_t NumElements_check = 1;
std::size_t NumElements = 1;
std::size_t RankRequired = 0;
std::vector<typename ETensor::Index> dimNonTrivial;
dimNonTrivial.reserve(dimData.size());
for( auto d : dimData ) {
NumElements_check *= d;
NumElements *= d;
if( d > 1 ) {
RankRequired++;
dimNonTrivial.push_back(d);
}
}
//if( RankRequired == 0 ) RankRequired++;
assert( NumElements_check == NumElements );
assert( NumElements == buf.size() && "Number of elements read back <> product of dimensions" );
// If our scalar object is a Container, make sure it's dimensions match what we read back
const auto InnerRank{Traits::rank_non_trivial};
if ( InnerRank > 0 ) {
assert( RankRequired >= InnerRank && "Tensor Container too complex for data" );
for( auto i = InnerRank - 1 ; i != -1 ; i-- ) {
auto d = dimNonTrivial[--RankRequired];
assert( d == Traits::DimensionNT(i) && "Tensor Container dimensions don't match data" );
NumElements /= d;
dimNonTrivial.pop_back();
}
}
// Make sure our object has the right rank
using Container = typename ETensor::Scalar;
const auto InnerRank = EigenIO::Traits<Container>::rank_non_trivial;
assert( ETensor::NumDimensions + InnerRank >= RankRequired );
assert( ETensor::NumDimensions >= RankRequired );
bool bShapeOK = true;
std::size_t RankNonTrivial = 0;
// Make sure fixed dimension objects have allocated memory
const auto & dims{output.dimensions()};
using ETDims = std::array<typename ETensor::Index, ETensor::NumDimensions>;
ETDims dimsNew;
// Make sure fixed dimension objects have allocated memory
/*if constexpr( EigenIO::is_tensor_fixed<ETensor>::value ) {
for( auto &d : dimsNew ) d = 0;
output( dimsNew ) = 0;
}*/
//const auto & dims{output.dimensions()};
for( auto i = 0, j = 0 ; bShapeOK && i < ETensor::NumDimensions ; i++ ) {
auto d = DimSize( output, i );
auto d = dims[i];
if( d < 1 )
bShapeOK = false;
else if( d > 1 ) {
@ -737,14 +757,14 @@ namespace Grid {
std::size_t idx = 0;
for( auto n = 0 ; n < NumElements ; n++ ) {
Container & c = output( MyIndex );
if constexpr( InnerRank == 0 ) {
if constexpr ( EigenIO::is_scalar<Container>::value ) {
c = buf[idx++];
} else {
for( Scalar & s : c )
s = buf[idx++];
}
// Now increment the index
for( int i = output.NumDimensions - 1; i >= 0 && ++MyIndex[i] == output.dimension(i); i-- )
for( int i = ETensor::NumDimensions - 1; i >= 0 && ++MyIndex[i] == dims[i]; i-- )
MyIndex[i] = 0;
}
}
@ -766,7 +786,7 @@ namespace Grid {
t.resize( dims );
}
template <typename T>
/*template <typename T>
template <typename ETensor>
typename std::enable_if<EigenIO::is_tensor_fixed<ETensor>::value, std::size_t>::type
Reader<T>::DimSize(ETensor &t, std::size_t dim )
@ -780,7 +800,7 @@ namespace Grid {
Reader<T>::DimSize(ETensor &t, std::size_t dim )
{
return t.dimension(dim);
}
}*/
template <typename T>
template <typename U>

63
tests/IO/Test_serialisation.cc
View File

@ -98,6 +98,8 @@ void ioTest(const std::string &filename, const O &object, const std::string &nam
bool good = Serializable::CompareMember(object, buf);
if (!good) {
std::cout << " failure!" << std::endl;
if constexpr (EigenIO::is_tensor<O>::value)
dump_tensor(buf,"???");
exit(EXIT_FAILURE);
}
std::cout << " done." << std::endl;
@ -109,21 +111,28 @@ typedef std::complex<double> TestScalar;
typedef Eigen::Tensor<TestScalar, 3, Eigen::StorageOptions::RowMajor> TestTensor;
typedef Eigen::TensorFixedSize<TestScalar, Eigen::Sizes<9,4,2>, Eigen::StorageOptions::RowMajor> TestTensorFixed;
typedef std::vector<TestTensorFixed> aTestTensorFixed;
typedef Eigen::TensorFixedSize<SpinColourVector, Eigen::Sizes<11,3,2>> LSCTensor;
typedef Eigen::TensorFixedSize<LorentzColourMatrix, Eigen::Sizes<5,7,2>> LCMTensor;
typedef Eigen::TensorFixedSize<SpinColourVector, Eigen::Sizes<11,3,2>, Eigen::StorageOptions::RowMajor> LSCTensor;
typedef Eigen::TensorFixedSize<LorentzColourMatrix, Eigen::Sizes<5,7,2>, Eigen::StorageOptions::RowMajor> LCMTensor;
// From Test_serialisation.cc
class ETSerClass: Serializable {
class PerambIOTestClass: Serializable {
public:
GRID_SERIALIZABLE_CLASS_MEMBERS(ETSerClass
, SpinColourVector, scv
, SpinColourMatrix, scm
, TestTensor, Critter
, TestTensorFixed, FixedCritter
, aTestTensorFixed, aFixedCritter
, LSCTensor, MyLSCTensor
, LCMTensor, MyLCMTensor
using PerambTensor = Eigen::Tensor<SpinColourVector, 6, Eigen::StorageOptions::RowMajor>;
GRID_SERIALIZABLE_CLASS_MEMBERS(PerambIOTestClass
//, SpinColourVector, scv
//, SpinColourMatrix, scm
, PerambTensor, Perambulator
, std::vector<std::string>, DistilParameterNames
, std::vector<int>, DistilParameterValues
//, TestTensor, Critter
//, TestTensorFixed, FixedCritter
//, aTestTensorFixed, aFixedCritter
//, LSCTensor, MyLSCTensor
//, LCMTensor, MyLCMTensor
);
ETSerClass() : Critter(7,3,2), aFixedCritter(3) {}
PerambIOTestClass() : Perambulator(2,3,1,4,5,1),
DistilParameterNames {"alpha", "beta", "gamma", "delta", "epsilon", "what's f?"},
DistilParameterValues{2,3,1,4,5,1}//, Critter(7,3,2), aFixedCritter(3)
{}
};
bool EigenIOTest(void) {
@ -157,7 +166,7 @@ bool EigenIOTest(void) {
Val += Inc;
}
ioTest<Hdf5Writer, Hdf5Reader, TestTensor>("iotest_tensor.h5", t, "eigen_tensor_instance_name");
dump_tensor(t, "t");
//dump_tensor(t, "t");
// Now serialise a fixed size tensor
using FixedTensor = Eigen::TensorFixedSize<TestScalar, Eigen::Sizes<8,4,3>>;
@ -170,11 +179,26 @@ bool EigenIOTest(void) {
Val += Inc;
}
ioTest<Hdf5Writer, Hdf5Reader, FixedTensor>("iotest_tensor_fixed.h5", tf, "eigen_tensor_fixed_name");
dump_tensor(tf, "tf");
//dump_tensor(tf, "tf");
PerambIOTestClass o;
for_all( o.Perambulator, [&](TestScalar &c, float f, const std::array<size_t,PerambIOTestClass::PerambTensor::NumIndices + EigenIO::Traits<SpinColourVector>::rank_non_trivial> &Dims ){
c = TestScalar{f,-f};
//std::cout << " a(" << Dims[0] << "," << Dims[1] << "," << Dims[2] << ")=" << c;
} );
dump_tensor(o.Perambulator, "PerambIOTestClass" );
/*for_all( o.FixedCritter, [&](TestScalar &c, float f, const std::array<size_t,TestTensorFixed::NumIndices> &Dims ){
c = TestScalar{f,-f};
//std::cout << " a(" << Dims[0] << "," << Dims[1] << "," << Dims[2] << ")=" << c;
} );
for( auto &z : o.aFixedCritter )
for_all( z, [&](TestScalar &c, float f, const std::array<size_t,TestTensorFixed::NumIndices> &Dims ){
c = TestScalar{f,-f};
//std::cout << " a(" << Dims[0] << "," << Dims[1] << "," << Dims[2] << ")=" << c;
} );*/
ioTest<Hdf5Writer, Hdf5Reader, PerambIOTestClass>("iotest_object.h5", o, "PerambIOTestClass_object_instance_name");
//DumpMemoryOrder(o.Perambulator);
ETSerClass o;
ioTest<Hdf5Writer, Hdf5Reader, ETSerClass>("iotest_object.h5", o, "ETSerClass_object_instance_name");
// Tensor of spin colour
LSCTensor l;
Val = 0;
@ -188,7 +212,7 @@ bool EigenIOTest(void) {
Val += Inc;
}
ioTest<Hdf5Writer, Hdf5Reader, LSCTensor>("iotest_LSCTensor.h5", l, "LSCTensor_object_instance_name");
dump_tensor(l, "l");
//dump_tensor(l, "l");
// Tensor of spin colour
LCMTensor l2;
@ -204,7 +228,8 @@ bool EigenIOTest(void) {
Val += Inc;
}
ioTest<Hdf5Writer, Hdf5Reader, LCMTensor>("iotest_LCMTensor.h5", l2, "LCMTensor_object_instance_name");
//dump_tensor(l2, "l2");
std::cout << "Wow!" << std::endl;
return true;

24
tests/hadrons/Test_hadrons_distil.cc
View File

@ -315,28 +315,30 @@ bool bNumber( int &ri, const char * & pstr, bool bGobbleWhiteSpace = true )
typedef Grid::Hadrons::MDistil::NamedTensor<Complex,3,sizeof(Real)> MyTensor;
void DebugShowTensor(MyTensor &x, const char * n)
template<typename T>
void DebugShowTensor(T &x, const char * n)
{
const MyTensor::Index s{x.size()};
std::cout << n << ".size() = " << s << std::endl;
std::cout << n << ".NumDimensions = " << x.NumDimensions << " (TensorBase)" << std::endl;
std::cout << n << ".NumIndices = " << x.NumIndices << std::endl;
const MyTensor::Dimensions & d{x.dimensions()};
std::cout << n << ".dimensions().size() = " << d.size() << std::endl;
const auto d{x.dimensions()};
//std::cout << n << ".dimensions().size() = " << d.size() << std::endl;
std::cout << "Dimensions are ";
for(auto i : d ) std::cout << "[" << i << "]";
for(auto i = 0; i < x.NumDimensions ; i++)
std::cout << "[" << d[i] << "]";
std::cout << std::endl;
MyTensor::Index SizeCalculated{1};
std::cout << "Dimensions again";
for(int i=0 ; i < d.size() ; i++ ) {
std::cout << " : [" << i << ", " << x.IndexNames[i] << "]=" << d[i];
for(int i=0 ; i < x.NumDimensions ; i++ ) {
std::cout << " : [" << i << /*", " << x.IndexNames[i] << */"]=" << x.dimension(i);
SizeCalculated *= d[i];
}
std::cout << std::endl;
std::cout << "SizeCalculated = " << SizeCalculated << std::endl;\
assert( SizeCalculated == s );
// Initialise
assert( d.size() == 3 );
assert( x.NumDimensions == 3 );
for( int i = 0 ; i < d[0] ; i++ )
for( int j = 0 ; j < d[1] ; j++ )
for( int k = 0 ; k < d[2] ; k++ ) {
@ -345,7 +347,7 @@ void DebugShowTensor(MyTensor &x, const char * n)
}
// Show raw data
std::cout << "Data follow : " << std::endl;
Complex * p = x.data();
typename T::Scalar * p = x.data();
for( auto i = 0 ; i < s ; i++ ) {
if( i ) std::cout << ", ";
std::cout << n << ".data()[" << i << "]=" << * p++;
@ -415,6 +417,10 @@ void DebugTestTypeEqualities(void)
bool DebugEigenTest()
{
{
Eigen::TensorFixedSize<std::complex<double>,Eigen::Sizes<3,4,5>> x;
DebugShowTensor(x, "fixed");
}
const char pszTestFileName[] = "test_tensor.bin";
std::array<std::string,3> as={"Alpha", "Beta", "Gamma"};
MyTensor x(as, 2,1,4);
@ -636,7 +642,7 @@ int main(int argc, char *argv[])
<< ", sizeof(std::size_t) = " << sizeof(std::size_t)
<< ", sizeof(std::streamsize) = " << sizeof(std::streamsize)
<< ", sizeof(Eigen::Index) = " << sizeof(Eigen::Index) << std::endl;
//if( DebugEigenTest() ) return 0;
if( DebugEigenTest() ) return 0;
if(DebugGridTensorTest()) return 0;
#endif